The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Autonomous driving systems and semi-autonomous driving systems utilize inputs regarding the road and other driving conditions to automatically control throttle and steering mechanisms. Accurate estimation and projection of a clear path over which to operate the vehicle is critical to successfully replacing the human mind as a control mechanism for vehicle operation.
Road conditions can be complex. Under normal operation of a vehicle, the human operator makes hundreds of observations per minute and adjusts operation of the vehicle on the basis of perceived road conditions. One aspect of perceiving road conditions is the perception of the road in the context of objects in and around the roadway and navigating a clear path through any objects. Replacing human perception with technology must include some means to accurately perceive objects and continue to effectively navigate around such objects.
Technological means for perceiving an object include data from visual cameras and radar imaging. Cameras translate visual images in the form of radiation such as light patterns or infrared signatures into a data format capable of being studied. One such data format includes pixelated images, in which a perceived scene is broken down into a series of pixels. Radar imaging utilizes radio waves generated by a transmitter to estimate shapes and objects present in front of the transmitter. Patterns in the waves reflecting off these shapes and objects can be analyzed and the locations of objects can be estimated.
Once data has been generated regarding the ground in front of the vehicle, the data must be analyzed to estimate the presence of objects from the data. Methods are known to study pixels in terms of comparing contrast between pixels, for instance identifying lines and shapes in the pixels and pattern recognition in which a processor may look for recognizable shapes in order to estimate an object represented by the shapes. By using cameras and radar imaging systems, ground or roadway in front of the vehicle can be searched for the presence of objects that might need to be avoided. However, the mere identification of potential objects to be avoided does not complete the analysis. An important component of any autonomous system includes how potential objects identified in perceived ground data are processed and manipulated to form a clear path in which to operate the vehicle.
One known method to form a clear path in which to operate the vehicle is to catalog and provisionally identify all perceived objects and form a clear path in light of the locations and behaviors of identified objects. Images may be processed to identify and classify objects according to their form and relationship to the roadway. While this method can be effective in forming a clear path, it requires a great deal of processing power, requiring the recognition and separation of different objects in the visual image, for instance, distinguishing between a tree along the side of the road and a pedestrian walking toward the curb. Such methods can be slow or ineffective to process complex situations or may require bulky and expensive equipment to supply the necessary processing capacity.